Analysis of Large Database Unbalanced Data Fragment Classification and Recognition Algorithm
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DOI: 10.25236/scmc.2019.072
Author(s)
Peng Mei, Tan Zerong, Hu Bibo
Corresponding Author
Peng Mei
Abstract
In view of the current development of big data era and the data processing of various industries, this paper proposes an unbalanced data fragment classification and recognition algorithm suitable for the current big data background. Firstly, the process of classification identification is explained in detail, and the problems existing in it are analyzed. The algorithm is described in detail, and the unbalanced data fragments are classified and identified. Experiments show that the classification and recognition algorithm can effectively improve the accuracy and lay a foundation for further research and development in this field.
Keywords
Big data era; Data processing; Unbalanced data fragment classification and recognition algorithm; Accuracy